FREQUENCY TO RAW

FREQUENCY TO RAW (LET)

LET Subcommand

Convert data in frequency format to raw format.

At times, data will be collected in a frequency format (i.e., a value with a count of how many times that value occurred). However, you may want to use Dataplot commands that expect the data to be given in a single column format. For example, if X = 2.3 has a count of 20, the value of 2.3 will simply be repeated 20 times.

Note that the maximum limit on the size of a Dataplot variables still applies. So if the sum of the counts array exceeds this limit, an error will be returned.

LET <y> = FREQUENCY TO RAW <xval> <count>
                        <SUBSET/EXPCEPT/FOR qualification>
where <xval> is a variable that contains the numeric values;
            <count> is a variable that contains the counts corresponding to <xval>;
            <y> is the variable to contain the raw data;
and where the <SUBSET/EXCEPT/FOR qualification> is optional.

LET Y = FREQUENCY TO RAW XVAL XFREQ

None

None

EXTEND	= Extends a variable by another variable.
LET	= Creates, transforms, etc. a variable.
STACK	= Convert a set of response variables to a single response variable and a tag variable.

Data Management

2004/5

 
READ xval freq
0  174
1  112
2  54
3  14
4  4
5  1
6  1
END OF DATA
LET Y = FREQUENCY TO RAW XVAL FREQ
HERMITE MAXIMUM LIKELIHOOD Y
    

The following output is generated.

  
             HERMITE PARAMETER ESTIMATION:
  
 NUMBER OF OBSERVATIONS                  =      360
 SAMPLE MINIMUM                          =    0.000000
 SAMPLE MAXIMUM                          =    6.000000
 SAMPLE MEAN                             =   0.8027778
 SAMPLE VARIANCE                         =   0.9665661
  
 METHOD OF MOMENTS
       ESTIMATE OF ALPHA                 =   0.4047077
       ESTIMATE OF BETA                  =    1.578891
       ESTIMATE OF A                     =   0.6389894
       ESTIMATE OF B                     =   0.8189416E-01
       ESTIMATE OF VARIANCE OF A         =   0.6960734E-02
       ESTIMATE OF VARIANCE OF B         =   0.1518932E-02
       ESTIMATE OF COVARIANCE OF A AND B =  -0.2587889E-02
  
 METHOD OF EVEN POINTS
       SUM OF EVEN FREQUENCIES           =    233.0000
       SUM OF ODD FREQUENCIES            =    127.0000
       ESTIMATE OF ALPHA                 =   0.4375446
       ESTIMATE OF BETA                  =    1.397189
       ESTIMATE OF A                     =   0.6113325
       ESTIMATE OF B                     =   0.9572265E-01
  
 METHOD OF ZERO FREQUENCY AND MEAN
       ZERO FREQUENCY                    =    174.0000
       ESTIMATE OF ALPHA                 =   0.3891761
       ESTIMATE OF BETA                  =    1.673586
       ESTIMATE OF A                     =   0.6513197
       ESTIMATE OF B                     =   0.7572901E-01
       ESTIMATE OF VARIANCE OF A         =   0.5608298E-02
       ESTIMATE OF VARIANCE OF B         =   0.1160128E-02
       ESTIMATE OF COVARIANCE OF A AND B =   0.1899538E-02
  
 METHOD OF MAXIMUM LIKELIHOOD
       ESTIMATE OF ALPHA                 =   0.3950545
       ESTIMATE OF BETA                  =    1.637014
       ESTIMATE OF A                     =   0.6467096
       ESTIMATE OF B                     =   0.7803404E-01
       ESTIMATE OF VARIANCE OF ALPHA     =   0.7677542E-02
       ESTIMATE OF VARIANCE OF BETA      =   0.2727334
       ESTIMATE OF COVARIANCE OF
       ALPHA AND BETA                    =  -0.4439158E-01